Incentives to Efficient Investment Decisions in Agricultural Cooperatives

Recent studies have questioned the competitiveness of agricultural cooperatives in an industrialized food system, based on empirical results and economic theory. New organizational institutions have been proposed to overcome the cooperative main weaknesses (the so called new generation cooperatives). In this paper, we provide a simple model based on a financial approach to address the issue of cooperative competitiveness and to assess the investment efficiency of both traditional and new generation cooperatives. The main conclusions of the analysis are: i) cooperatives (both traditional and new generation ones) may have incentive to adopt projects that do not maximize the Net Present Value of the firm ii) the institutions of new generation cooperatives are not sufficient to ensure net present value maximization, even though they address some of the main concerns of traditional cooperatives iii) traditional cooperatives may have a competitive advantage in businesses that require the aggregation of a large number of farmers.agricultural cooperatives, investment efficiency, Agribusiness, Agricultural Finance, Q13, Q14,

The Crisis of Small Farms in Central Italy: Can Farmer Turnover Slow Down the Downfall?

We use original data to assess if the current incentives to farmer turnover may help the competitiveness of small farms in the Lazio Region (central Italy). Our results show that substantial changes in the policy may be needed. The paper analyzes sharp declining trend in small farm number, discusses its causes and evaluates the policies that have been adopted to stop or slow down this downfall. The regional policy makers consider the ageing of the farmers is a key determinant of the decline of small farms. Consequently, they have designed an incentive policy to generational turnover mainly based on installation payments. Given our empirical findings we conclude that this policy may fail to achieve the stated objectives. Firstly, farms that had a generational turnover in the last seven years do not show higher propensity to investment than the control group. These results suggest that farmers’ turnover per se may fail to increase the competitiveness of small farms. Secondly, in almost half of the cases the change in ownership is the result of a long process. Thus the timing of the policy may be wrong. Thirdly the policy is difficult to monitor and opportunistic behavior is possible.Generational turnover in Agriculture, Installation payments, Agricultural and Food Policy, Q10, Q18,

Synthesis of Statistical Indicators to Evaluate Quality of Life in the Italian Provinces

This work remarks the need to carefully evaluate the real importance of each variable used in a multivariate analysis context, with particular regard to cases when an overall performance ranking is the main final purpose. In particular, both a preliminary transformation of variables – aimed at reducing asymmetry and variability of their variation ranges – and the evaluation of their intrinsic explicative power – through redundancy analysis and weighting methods – are proposed. Theoretical and empirical considerations are developed in the frame of quality of life evaluation, carried out at the Italian provinces level on the basis of a yearly survey managed by the Italian economic newspaper "Il Sole24ore". A particular emphasis is given to some normalisation criteria and the case when original variables are grouped "a priori" into logical blocks. A final comparison between the actual ranking method and a series of alternatives is proposed as well.multivariate analysis, principal components analysis, ranking, redundant variable, weighing system.

Modelling Pricing Behavior with Weak A‐Priori Information: Exploratory Approach

In the absence of reliable a priori information, choosing the appropriate theoretical model to describe an industry’s behavior is a critical issue for empirical studies about market power. A wrong choice may result in model misspecification and the conclusions of the empirical analysis may be driven by the wrong assumption about the behavioral model.This paper develops a methodology aimed to reduce the risk of misspecification bias. The approach is based on the sequential application of a sliced inverse regression (SIR) and a nonparametric Nadaraya/ Watson regression (NW). The SIR‐NW algorithm identifies the factors affecting pricing behavior in an industry and provides a nonparametric characterization of the function linking these variables to price. This information may be used to guide the choice of the model specification for a parametric estimation of market power.The SIR NW algorithm is designed to complement the estimation of structural models of market behavior, rather than to replace it. The value of this methodology for empirical industrial organization studies lies in its data driven approach that does not rely on prior knowledge of the industry. The method reverses the usual hypothesis testing approach. Instead of first choosing the model based on a priori information and then testing if it is compatible with the data, the econometrician selects a theoretical model based on the observed data. Thus, the methodology is particularly suited for those cases where the researcher has no a priori information about the behavioral model, or little confidence in the information that is available

EFFECTS OF MANAGERS' POWER ON CAPITAL STRUCTURE: A STUDY ON ITALIAN AGRICULTURAL COOPERATIVES

Agribusiness,

Data in Business Process Models. A Preliminary Empirical Study

Traditional activity-centric process modeling languages treat data as simple black boxes acting as input or output for activities. Many alternate and emerging process modeling paradigms, such as case handling and artifact-centric process modeling, give data a more central role. This is achieved by introducing lifecycles and states for data objects, which is beneficial when modeling data-or knowledge-intensive processes. We assume that traditional activity-centric process modeling languages lack the capabilities to adequately capture the complexity of such processes. To verify this assumption we conducted an online interview among BPM experts. The results not only allow us to identify various profiles of persons modeling business processes, but also the problems that exist in contemporary modeling languages w.r.t. The modeling of business data. Overall, this preliminary empirical study confirms the necessity of data-awareness in process modeling notations in general

Hybrid Simulation and Test of Vessel Traffic Systems on the Cloud

This paper presents a cloud-based hybrid simulation platform to test large-scale distributed System-of-Systems (SoS) for the management and control of maritime traffic, the so-called Vessel Traffic Systems (VTS). A VTS consists of multiple, heterogeneous, distributed and interoperating systems, including radar, automatic identification systems, direction finders, electro-optical sensors, gateways to external VTSs, information systems; identifying, representing and analyzing interactions is a challenge to the evaluation of the real risks for safety and security of the marine environment. The need for reproducing in fabric the system behaviors that could occur in situ demands for the ability of integrating emulated and simulated environments to cope with the different testability requirements of involved systems and to keep testing cost sustainable. The platform exploits hybrid simulation and virtualization technologies, and it is deployable on a private cloud, reducing the cost of setting up realistic and effective testing scenarios